Home > Mateda2.0 > learning > LearnGaussianFullModel.m

LearnGaussianFullModel

PURPOSE ^

[model] = LearnGaussianFullModel(k,NumbVar,Card,AuxPop,AuxFunVal,learning_params)

SYNOPSIS ^

function [model] = LearnGaussianFullModel(k,NumbVar,Card,AuxPop,AuxFunVal,learning_params)

DESCRIPTION ^

 [model] = LearnGaussianFullModel(k,NumbVar,Card,AuxPop,AuxFunVal,learning_params)
 LearnGaussianFullModel:     Learns a full multivariate Gaussian model 
 INPUTS
 k: Current generation
 NumbVar: Number of variables
 Card: Vector with the range of values for all the variables. 
 AuxPop:  Population from which the model is learned  
 AuxFunVal: Evaluation of the data set (required for some learning algorithms, not for this one)
 OUTPUTS
 model: model{1} = mean of the variables
        model{2} = covariance of the variables 

 Last version 8/26/2008. Roberto Santana (roberto.santana@ehu.es)

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function [model] = LearnGaussianFullModel(k,NumbVar,Card,AuxPop,AuxFunVal,learning_params)
0002 % [model] = LearnGaussianFullModel(k,NumbVar,Card,AuxPop,AuxFunVal,learning_params)
0003 % LearnGaussianFullModel:     Learns a full multivariate Gaussian model
0004 % INPUTS
0005 % k: Current generation
0006 % NumbVar: Number of variables
0007 % Card: Vector with the range of values for all the variables.
0008 % AuxPop:  Population from which the model is learned
0009 % AuxFunVal: Evaluation of the data set (required for some learning algorithms, not for this one)
0010 % OUTPUTS
0011 % model: model{1} = mean of the variables
0012 %        model{2} = covariance of the variables
0013 %
0014 % Last version 8/26/2008. Roberto Santana (roberto.santana@ehu.es)
0015  
0016        
0017      model{1} =  mean(AuxPop);   % Vector of means
0018      model{2} =  cov(AuxPop);    % Vector of covariances
0019       
0020      return;
0021        
0022        
0023

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